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In the Zhouqu region (Gansu, China), landslide distribution and activity exploits geological weaknesses in the faultcontrolled belt of low-grade metamorphic rocks of the Bailong valley and severely impacts lives and livelihoods in this region. Landslides reactivated by the Wenchuan 2008 earthquake and debris flows triggered by rainfall, such as the 2010 Zhouqu debris flow, have caused more than 1700 casualties and estimated economic losses of some US$0.4 billion. Earthflows presently cover some 79% of the total landslide area and have exerted a strong influence on landscape dynamics and evolution in this region. In this study, we use multi-temporal Advanced Land Observing Satellite and Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) data and time series interferometric synthetic aperture radar to investigate slow-moving landslides in a mountainous region with steep topography for the period December 2007-August 2010 using the Small Baseline Subsets (SBAS) technique. This enabled the identification of 11 active earthflows, 19 active landslides with deformation rates exceeding 100 mm/year and 20 new instabilities added into the pre-existing landslide inventory map. The activity of these earthflows and landslides exhibits seasonal variations and accelerated deformation following the Wenchuan earthquake. Time series analysis of the Suoertou earthflow reveals that seasonal velocity changes are characterized by comparatively rapid acceleration and gradual deceleration with distinct kinematic zones with different mean velocities, although velocity changes appear to occur synchronously along the landslide body over seasonal timescales. The observations suggest that the post-seismic effects (acceleration period) on landslide deformation last some 6-7 months.

We present how to detect reservoirs by the 3‐D normalized full gradient (NFG) of gravity anomalies constrained by seismic and drilling data. The normalized full gradient represents the full gradient of the gravity anomaly at a point divided by the average of the full gradient at the datum. The closed minima on an NFG map indicate the occurrence and horizontal locations of the centers of mass of density anomalies related to oil reservoirs. This information can be used to select well locations in an oil field. On a cross‐section, the closed minima can be used to estimate the depth to centers of mass of possible hydrocarbon reservoirs. Some characteristics of the NFG are calculated for a hypothetical case of an anticline saturated with oil and gas. The relationship of these characteristics to the geometry and physical parameters of the anticline is studied. Modeling studies show that the NFG largely depends on the number of terms in the Fourier series used to calculate it, and it closely related to the length of the gravity profile or the size of the study area. Applying the NFG method to the Shengli oil field, i.e., using closed minima of NFG alongside drilling data, showed an effectiveness of up to 70%. These results were used to select well locations with the result that some high‐production gas‐bearing strata were discovered by drilling.

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Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization.

Human body orientation estimation from microinertial/magnetic sensor units is highly important for synthetic environments, robotics, and other human-computer interaction applications. In practice, the main challenge is how to deal with linear acceleration interference and magnetic disturbance which always cause significant attitude-estimation errors. In this paper, we present a novel quaternion-based Kalman filter with vector selection scheme for accurate human body orientation estimation using an inertial/magnetic sensor unit. In the proposed algorithm, the gyroscope measurement is used as an input to construct the linear process equation, and the accelerometer and magnetometer measurements are manipulated to establish the linear pseudomeasurement equation. A linear Kalman filter is then deployed to estimate the body orientation. In the Kalman filter framework, a vector selection scheme is designed to protect the algorithm against undesirable conditions such as temporary intensive movement and magnetic disturbance and enable it to acquire more accurate orientation estimation. The experimental results have shown that the proposed algorithm can provide accurate attitude estimations with regard to the ground truth.